Generate list

[Irini Yacoub]

I did the stcurve command for a cumulative incidence curve looking at cumulative incidence of failure (status=1), with death as a competing risk (status=2), comparing two types of chemotherapy (ifp 0 1). How do i generate a list of these curves looking at incidence by time in 12 month intervals?

[Hemanshu Kumar]

Welcome to Statalist, Irini!

Would you be kind enough to show us an extract of your data using the dataex command, as well as the current code you are running to generate the curves? See also the Statalist FAQ on how to pose questions more effectively, especially point #12.

[Irini Yacoub]

[CODE]
* Example generated by -dataex-. For more info, type help dataex
clear
input byte ifp int dftime byte(stat _st _d) int _t byte _t0
1 93 0 1 0 93 0
0 157 0 1 0 157 0
0 121 2 1 0 121 0
0 55 2 1 0 55 0
0 60 0 1 0 60 0
0 159 2 1 0 159 0
0 15 2 1 0 15 0
0 42 2 1 0 42 0
0 94 2 1 0 94 0
0 29 2 1 0 29 0
0 69 0 1 0 69 0
0 10 1 1 1 10 0
1 15 1 1 1 15 0
0 68 2 1 0 68 0
0 63 0 1 0 63 0
0 52 2 1 0 52 0
0 29 2 1 0 29 0
0 22 1 1 1 22 0
0 19 2 1 0 19 0
0 57 0 1 0 57 0
0 49 2 1 0 49 0
0 12 1 1 1 12 0
0 60 0 1 0 60 0
0 54 0 1 0 54 0
0 53 0 1 0 53 0
0 44 0 1 0 44 0
0 184 0 1 0 184 0
0 43 0 1 0 43 0
0 6 1 1 1 6 0
0 59 0 1 0 59 0
0 45 0 1 0 45 0
1 83 0 1 0 83 0
1 20 0 1 0 20 0
0 108 0 1 0 108 0
0 62 0 1 0 62 0
0 63 0 1 0 63 0
0 58 0 1 0 58 0
0 56 0 1 0 56 0
0 46 2 1 0 46 0
0 196 2 1 0 196 0
0 60 0 1 0 60 0
0 150 0 1 0 150 0
0 47 0 1 0 47 0
0 45 0 1 0 45 0
0 44 0 1 0 44 0
0 67 2 1 0 67 0
0 44 0 1 0 44 0
0 6 2 1 0 6 0
0 52 2 1 0 52 0
0 42 0 1 0 42 0
0 38 0 1 0 38 0
0 35 1 1 1 35 0
1 24 0 1 0 24 0
0 24 0 1 0 24 0
0 110 2 1 0 110 0
0 112 2 1 0 112 0
0 3 0 1 0 3 0
1 85 1 1 1 85 0
0 112 0 1 0 112 0
0 156 0 1 0 156 0
1 143 2 1 0 143 0
1 44 1 1 1 44 0
0 99 2 1 0 99 0
0 51 0 1 0 51 0
1 162 2 1 0 162 0
0 0 0 0 . . .
1 17 0 1 0 17 0
1 3 0 1 0 3 0
1 18 0 1 0 18 0
0 47 2 1 0 47 0
0 16 0 1 0 16 0
0 26 2 1 0 26 0
0 16 0 1 0 16 0
0 16 0 1 0 16 0
1 71 0 1 0 71 0
0 35 1 1 1 35 0
0 69 2 1 0 69 0
1 59 0 1 0 59 0
0 52 2 1 0 52 0
1 73 0 1 0 73 0
1 72 0 1 0 72 0
1 64 0 1 0 64 0
1 71 0 1 0 71 0
0 249 0 1 0 249 0
0 248 0 1 0 248 0
0 118 0 1 0 118 0
0 62 0 1 0 62 0
0 22 0 1 0 22 0
0 58 2 1 0 58 0
0 140 0 1 0 140 0
1 0 2 0 . . .
0 201 0 1 0 201 0
0 43 0 1 0 43 0
0 9 0 1 0 9 0
0 218 0 1 0 218 0
0 162 0 1 0 162 0
0 156 0 1 0 156 0
0 25 0 1 0 25 0
0 92 0 1 0 92 0
0 71 0 1 0 71 0
end
stcrreg ifp, compete(stat==2)

Failure _d: stat==1
Analysis time _t: dftime

Iteration 0: Log pseudolikelihood = -235.03074
Iteration 1: Log pseudolikelihood = -235.03036
Iteration 2: Log pseudolikelihood = -235.03036

Competing-risks regression No. of obs = 336
No. of subjects = 336
Failure event: stat == 1 No. failed = 42
Competing event: stat == 2 No. competing = 59
No. censored = 235

Wald chi2(1) = 0.22
Log pseudolikelihood = -235.03036 Prob > chi2 = 0.6399

[Irini Yacoub]

stcurve, cif at(ifp=(0 1))